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Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The high mortality rate associated with coronary heart disease (CHD) has driven intensive research in cardiac imaging and image analysis. The advent of computed tomography angiography (CTA) has turned non-invasive diagnosis ...

Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks.

Scientific reports
Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed g...

Iterative Learning Impedance for Lower Limb Rehabilitation Robot.

Journal of healthcare engineering
This paper discusses the problem of squatting training of stroke patients. The main idea is to correct the patient's training trajectory through an iterative learning control (ILC) method. To obtain better rehabilitation effect, a patient will typica...

A multi-perspective evaluation of a service robot for seniors: the voice of different stakeholders.

Disability and rehabilitation. Assistive technology
PURPOSE: The potential of service robots for seniors is given increasing attention as the ageing population in Western countries will continue to grow as well as the demand for home care. In order to capture the experience of living with a robot at h...

Ultrasound image-based thyroid nodule automatic segmentation using convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Delineation of thyroid nodule boundaries from ultrasound images plays an important role in calculation of clinical indices and diagnosis of thyroid diseases. However, it is challenging for accurate and automatic segmentation of thyroid nodul...

TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

Scientific reports
Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical n...

Recognition of normal-abnormal phonocardiographic signals using deep convolutional neural networks and mel-frequency spectral coefficients.

Physiological measurement
UNLABELLED: Intensive care unit patients are heavily monitored, and several clinically-relevant parameters are routinely extracted from high resolution signals.

Combining sparse coding and time-domain features for heart sound classification.

Physiological measurement
OBJECTIVE: This paper builds upon work submitted as part of the 2016 PhysioNet/CinC Challenge, which used sparse coding as a feature extraction tool on audio PCG data for heart sound classification.
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Infrastructural intelligence: Contemporary entanglements between neuroscience and AI.

Progress in brain research
In this chapter, I reflect on contemporary entanglements between artificial intelligence and the neurosciences by tracing the development of Google's recent DeepMind algorithms back to their roots in neuroscientific studies of episodic memory and ima...